Generating synthetic benchmark circuits for accelerated life testing of field programmable gate arrays using genetic algorithm and particle swarm optimization

Accelerated life testing (ALT) of a field programmable gate array (FPGA) requires it to be configured with a circuit that satisfies multiple criteria. Hand-crafting such a circuit is a herculean task as many components of the criteria are orthogonal to each other demanding a complex multivariate optimization. This paper presents an evolutionary algorithm aided by particle swarm optimization methodology to generate synthetic benchmark circuits (SBC) that can be used for ALT of FPGAs. The proposed algorithm was used to generate a SBC for ALT of a commercial FPGA. The generated SBC when compared with a hand-crafted one, demonstrated to be more suitable for ALT, measured in terms of meeting the multiple criteria. The SBC generated by the proposed technique utilizes 8.37% more resources; operates at a maximum frequency which is 40% higher; and has 7.75% higher switching activity than the hand-crafted one reported in the literature. The hand-crafted circuit is very specific to the particular device of that family of FPGAs, whereas the proposed algorithm is device-independent. In addition, it took several man months to hand-craft the SBC, whereas the proposed algorithm took less than half-a-day.     

Genetic algorithm and self organizing map based fuzzy hybrid intelligent method for color image segmentation

The grouping of pixels based on some similarity criteria is called image segmentation. In this paper the problem of color image segmentation is considered as a clustering problem and a fixed length genetic algorithm (GA) is used to handle it. The effectiveness of GA depends on the objective function (fitness function) and the initialization of the population. A new objective function is proposed to evaluate the quality of the segmentation and the fitness of a chromosome. In fixed length genetic algorithm the chromosomes have same length, which is normally set by the user. Here, a self organizing map (SOM) is used to determine the number of segments in order to set the length of a chromosome automatically. An opposition based strategy is adopted for the initialization of the population in order to diversify the search process. In some cases the proposed method makes the small regions of an image as separate segments, which leads to noisy segmentation. A simple ad hoc mechanism is devised to refine the noisy segmentation. The qualitative and quantitative results show that the proposed method performs better than the state-of-the-art methods.     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

Optimal strategies for manufacturing/remanufacturing system with the consideration of recycled products

This paper analyzes the model of the recycled products which are considered with the minimum quality level in manufacturing/remanufacturing system. In this model, a constant demand is satisfied by manufacturing raw materials and remanufacturing recycled products which are up to the quality level. It is assumed that functions of recycling rate, buyback cost and remanufacturing cost are depend on the minimum quality level. The quality level of recycled products is set to be exponential distribution and then the model is established. The results show that when the buyback cost is low (the quality of the recycled products is low), the average total cost is low, though the remanufacturing cost is high. Namely, the companies are willing to recycle the used products with low quality level. Meanwhile, the optimal strategy of recycling, manufacturing and remanufacturing is investigated here. Through construction of a solution process on Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and numerical examples with sensitive analysis, the validity of the model has been proved.     

Carbon nanotube–polyaniline composites

The last decade has seen a growing interest in hybrid electrically conducting nanocomposites. This article aims to provide a detailed overview of the present status of research in carbon nanotube–polyaniline (CNT/PANI) composites, from processing to structural and property evaluations. CNT/PANI are synthesized by electrochemical and chemical processing. When chemical methods are used, the main challenge is to obtain processable CNT/PANI in the emeraldine salt (ES) form composites. Stable dispersions of ES–CNT in organic media are prepared using the post doping method, inverse emulsion polymerization, or ex situ polymerizations. On the contrary, stable water dispersions of CNT/ES are prepared using hydrophilization of a preformed CNT/ES composite, direct synthesis of micelle–CNT hybrid templates, interfacial polymerization, covalent functionalization of CNT with a water soluble polymer, or using electrostatic interactions between two oppositely charged ES and CNT aqueous colloids. Moreover, the strategies for the synthesis of ternary CNT/PANI composites incorporating noble metal nanoparticles, metal oxide, or graphene sheets are also presented and analyzed in depth. Finally, we give a review of potential applications, including chemical sensors, capacitors, fuel cells and electronic devices.     

基于改进的GA-ELM煤与瓦斯突出预测模型

为准确、快速地预测煤与瓦斯突出,提出了一种基于因子分析和遗传算法(GA)优化极限学习机(ELM)的煤与瓦斯突出危险性预测模型。构建10种影响因素的煤与瓦斯突出评价指标体系,采用因子分析法对评价指标体系进行分析提取,将提取出的5个公因子作为ELM的输入参数,为避免ELM输入权值和隐含层偏差随机性的影响,应用GA对ELM模型参数进行优化,构建GA-ELM模型,选取20组实例进行仿真预测,同时与传统单一的ELM、SVM和BP模型进行对比分析。结果表明:基于改进的GA-ELM模型能有效降低数据冗余、简化网络结构和提高判别精度,提出将其运用到煤与瓦斯突出的预测与实际结果具有很好的一致性。     

电梯智能群控系统研究概况

电梯是高楼大厦中不可缺少的垂直运输工具。为了提高电梯服务的性能,采用优质的电梯群控系统统一管理电梯运行是一个值得研究的问题。本文介绍了电梯群控系统的起源和现状,着重对智能群控技术发展进行了概括和分析。对部分电梯公司的群控技术应用情况进行了论述。最后对群控技术的发展进行了展望。     

Optimization of indoor climate conditioning with passive and active methods using GA and CFD

This study aims at the development of an optimal design tool using a genetic algorithm (GA) and computational fluid dynamics (CFD). Random variables (fluctuating outdoor conditions), passive design elements (model variables) and active design elements (HVAC system) were set up to represent a realistic building environment. A combination of designs is determined based on the relationship between fluctuating outdoor conditions and the HVAC system in the optimal design search. Building environment designs should consider both active and passive design elements because the HVAC system keeps adjusting the supply air flow rate until the indoor climate reaches target conditions when outdoor conditions are changing.     

考虑“风-光-荷-储”联合运行的配电网双层规划方法

分布式电源与储能系统在配电网中的应用是当前研究的热点。提出了一种风机、光伏电源、储能系统在配电网中的双层规划模型。上层模型以投资、运维费用为优化目标,同时考虑区域的购电费用及网损费用,完成风机和光伏电源的容量配置;下层模型提出了一种储能系统削峰填谷的运行策略,基于该策略完成储能系统的选址定容工作。针对以上模型,提出以下求解方法:基于遗传算法求解上层模型,并通过K均值聚类方法对比研究输入数据序列长度对规划结果的影响,通过帕累托分析研究了投资运维费用与购电费用及网损费用的关系;使用YALMIP工具箱完成储能系统运行策略的求解,进而完成储能系统的选址定容工作。最后,通过IEEE-33节点标准配电系统仿真验证了所提模型在风机和光伏电源以及储能系统规划方面的有效性,结果显示所提储能运行策略具有良好的削峰填谷效果。